Exploring the Influence of 34S Fractionation From Emission Sources and SO2 Atmospheric Oxidation on Sulfate Source Apportionment Based on Hourly Resolution δ34S‐SO2/SO42−. Issue 8 (24th April 2023)

• Record Type: Journal Article
• Authors: Feng, Xinxin; Chen, Yingjun; Liu, Zeyu; Feng, Yanli; Du, Huiyun; Mu, Yujing; Chen, Jianmin
• Is Part Of: Journal of geophysical research. Volume 128:Issue 8(2023)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2023-04-24
• Subjects: sulfur isotope -- source apportionment -- fractionation effects -- high time resolution; Atmospheric physics -- Periodicals; Geophysics -- Periodicals; 551.5
• DOI: 10.1029/2023JD038595
• Languages: English
• ISSNs: 2169-897X

Abstract

Abstract: Sulfate (SO4 2− ) sources are unclear leading to the underestimation of its concentration in the model. Hourly resolution δ 34 S‐SO2 and δ 34 S‐SO4 2− values of three haze episodes (EP1‐EP3) were synchronously collected for the first time to quantify the influence of 34 S fractionation from emission sources (e.g., coal combustion) and SO2 atmospheric oxidation on SO2 /SO4 2− source apportionment. After considering the 34 S fractionation from coal combustion and atmospheric oxidation, the reasonable and logical source contributions of SO4 2− were obtained, showing highly consistent with that of Positive Matrix Factorization model results. Considering the 34 S fraction from atmospheric oxidation, the source apportionment of SO2 /SO4 2− obtained by hourly resolution δ 34 S‐SO2 and δ 34 S‐SO4 2− can more accurately reflect the dynamic changes of emission sources. Traffic emissions (49%) and coal combustion (46%–65%) were the major contributors to SO2 /SO4 2− in EP1 and EP2‐EP3, respectively. However, obvious deviations of coal combustion contribution were found without considering 34 S fractionation from coal combustion. Especially for the northwest transmission channels in EP2‐EP3, the deviation values accounted for 17.1%–38.5% of secondary SO4 2− . Moreover, δ 34 S was considered as a more sensitive source indicator than SO2 concentration by the results comparison of 34 S technique and air quality model (Nested Air Quality Prediction Model System), which can provide more reliable evidence for SO2 emission control. Plain Language Summary: Inadequate understanding of sulfate (SO4 2− ) sources leads to the deviation of its concentration prediction in the model. Based on the hourly resolution δ 34 S values of SO2 and SO4 2− during three haze episodes, this study investigated the influence of 34 S fractionation from emission sources and the SO2 oxidation process on the source contributions of SO4 2− . We found that the source contributions of SO4 2− were more reasonable when considered the 34 S fractionation from coal combustion and SO2 atmospheric oxidation, which were similar to the results of Positive Matrix Factorization model. Considering the 34 S fractionation from SO2 oxidation process, we also obtained the dynamic source contributions of SO4 2− in haze episodes, showing traffic emission (49%) and coal combustion (46%–65%) as the major contributors to SO4 2− in EP1 and EP2‐EP3, respectively. Otherwise, ignoring the 34 S fractionation from coal combustion, the contribution of coal combustion to SO4 2− showed great deviations (17.1%–38.5% of secondary SO4 2− ). Finally, the result comparisons of SO4 2− sources between 34 S and air quality model showed 34 S as a more sensitive source indicator than SO2 concentration to trace the source emission and make emission reduction measures in the future. Key Points: Reasonable and logical source contributions of SO4 2− were obtained with considering the 34 S fractionation effects from coal combustion and atmospheric oxidation processes Evidence from 34 S showed that traffic emission and coal combustion were major contributors to SO4 2− in EP1 and EP2‐EP3, respectively Compared with SO2 concentration, 34 S is a more sensitive index to trace the SO2 /SO4 2− emission sources in the future